microgrid controller and advanced distribution management ... · microgrid controller and advanced...
TRANSCRIPT
ORNL/TM-2016/288
Microgrid Controller and Advanced Distribution Management System Survey Report
Guodong Liu Michael R. Starke Drew Herron
July 2016
Approved for public release. Distribution is unlimited.
DOCUMENT AVAILABILITY
Reports produced after January 1, 1996, are generally available free via US Department of Energy (DOE) SciTech Connect. Website http://www.osti.gov/scitech/ Reports produced before January 1, 1996, may be purchased by members of the public from the following source: National Technical Information Service 5285 Port Royal Road Springfield, VA 22161 Telephone 703-605-6000 (1-800-553-6847) TDD 703-487-4639 Fax 703-605-6900 E-mail [email protected] Website http://www.ntis.gov/help/ordermethods.aspx
Reports are available to DOE employees, DOE contractors, Energy Technology Data Exchange representatives, and International Nuclear Information System representatives from the following source: Office of Scientific and Technical Information PO Box 62 Oak Ridge, TN 37831 Telephone 865-576-8401 Fax 865-576-5728 E-mail [email protected] Website http://www.osti.gov/contact.html
This report was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof.
ORNL/TM-2016/288
Electrical and Electronic Systems Research Division
Microgrid Controller and Advanced Distribution Management System Survey Report
Guodong Liu
Michael R. Starke
Drew Herron
Date Published: July 2016
Prepared by
OAK RIDGE NATIONAL LABORATORY
Oak Ridge, TN 37831-6283
managed by
UT-BATTELLE, LLC
for the
US DEPARTMENT OF ENERGY
under contract DE-AC05-00OR22725
iii
CONTENTS
LIST OF FIGURES ...................................................................................................................................... v LIST OF TABLES ........................................................................................................................................ v ACRONYMS .............................................................................................................................................. vii ABSTRACT .................................................................................................................................................. 1 1. INTRODUCTION ................................................................................................................................ 1
1.1 MICROGRIDS ........................................................................................................................... 1 1.2 MICROGRID CONTROLLER .................................................................................................. 1 1.3 ADVANCED DISTRIBUTION MANAGEMENT SYSTEM ................................................... 2 1.4 SCOPE AND PURPOSE ............................................................................................................ 3 1.5 CHALLENGES .......................................................................................................................... 3
2. MICROGRID CONTROLLER SURVEY ........................................................................................... 4 2.1 APPROACH ............................................................................................................................... 4 2.2 SURVEY RESULTS ................................................................................................................ 10
CONCLUSION ........................................................................................................................................... 12 REFERENCES ........................................................................................................................................... 13 APPENDIX A. MICROGRID FUNCTION DEFINITIONS ................................................................... A-1 APPENDIX B. MICROGRID FUNCTIONS COMPARISON ENERGY MANAGEMENT ................. B-1 APPENDIX C. MICROGRID FUNCTIONS PROTECTION AND CONTROL .................................... C-1 APPENDIX D. MICROGRID FUNCTIONS RESILENCY .................................................................... D-1 APPENDIX E. MICROGRID FUNCTIONS ANCILLARY SERVICES ............................................... E-1 APPENDIX F. MICROGRID FUNCTIONS GRAPHICAL USER INTERFACE AND DATA
MANAGEMENT .............................................................................................................................. F-1
v
LIST OF FIGURES
Fig. 1. A typical DMS. .................................................................................................................................. 3 Fig. 2. Microgrid functions. .......................................................................................................................... 5 Fig. 3. Sample screenshot from survey. ...................................................................................................... 10
LIST OF TABLES
Table 1. Functions in energy management group ......................................................................................... 6 Table 2. Functions in protection and control group ...................................................................................... 7 Table 3. Functions in resiliency group .......................................................................................................... 7 Table 4. Functions in ancillary services group ............................................................................................. 8 Table 5. Functions in data management group ............................................................................................. 8 Table 6. Survey participants ......................................................................................................................... 9
vii
ACRONYMS
ADMS Advanced Distribution Management System
CSEISMIC Complete System-level Efficient and Interoperable Solution for Microgrid Integrated
Controls
DDS Data Distribution Service
DER distributed energy resource
DG distributed generation
DMS distribution management system
DOE US Department of Energy
EMS energy management system
IEEE Institute of Electrical and Electronics Engineers
OMS outage management system
ORNL Oak Ridge National Laboratory
R&D research and development
SCADA supervisory control and data acquisition
UPS uninterruptible power supply
1
ABSTRACT
A microgrid controller, which serves as the heart of a microgrid, is responsible for optimally managing
the distributed energy resources, energy storage systems, and responsive demand and for ensuring the
microgrid is being operated in an efficient, reliable, and resilient way. As the market for microgrids has
blossomed in recently years, many vendors have released their own microgrid controllers to meet the
various needs of different microgrid clients. However, due to the absence of a recognized standard for
such controllers, vendor-supported microgrid controllers have a range of functionalities that are
significantly different from each other in many respects. As a result the current state of the industry has
been difficult to assess. To remedy this situation the authors conducted a survey of the functions of
microgrid controllers developed by vendors and national laboratories. This report presents a clear
indication of the state of the microgrid-controller industry based on analysis of the survey results. The
results demonstrate that US Department of Energy–funded research in microgrid controllers is unique and
not competing with that of industry.
1. INTRODUCTION
1.1 MICROGRIDS
The growth of distributed renewable and/or nonrenewable energy resource installations, emerging utility-
scale energy storage, plug-in hybrid electric vehicle use, and demand response is bringing unprecedented
opportunities and challenges to the electric distribution system. As these technologies evolve, utilities,
end users, manufacturers, and other participants in distribution system operations are actively
transforming the utility operational model. In the past, utility systems were able to mostly operate in
isolation, but they are now facing a systems-integration challenge with the complex coordination and
integration necessary for these distributed resources.
One available approach for integrating these technologies is through a microgrid. As defined by the
Microgrid Exchange Group, “A microgrid is a group of interconnected loads and distributed energy
resources within clearly defined electrical boundaries that acts as a single controllable entity with respect
to the grid. A microgrid can connect and disconnect from the grid to enable it to operate in both grid-
connected or island-mode.”[1] This definition of a microgrid has been adopted by the US Department of
Energy (DOE) as well as the Electric Power Research Institute. Under this definition a microgrid can be
regarded as a controllable resource connected to a distribution network.
With a microgrid, power can be imported or exported to the main distribution network depending on the
system constraints and the economic incentives (e.g., market tariffs). A microgrid can also provide
ancillary services such as voltage support and regulation services in support of the main distribution grid
or utility. This is a feature that a conventional end-user system cannot deliver [2, 3]. Furthermore, a
microgrid not only provides energy but also improves local reliability, reduces emissions, and contributes
to a lower cost for the energy supply by taking advantage of distributed energy resources (DERs), storage
devices, and responsive loads [4]. In addition, a microgrid can improve power quality by supporting
voltage and reducing voltage dips within the microgrid [5]. These benefits also support the end-use
customers and have attracted growing attention from both academia and industry [6].
1.2 MICROGRID CONTROLLER
Achieving the various described benefits from a microgrid requires a coordinated and coherent operation
of the microgrid assets including DERs, energy storage systems, and responsive load. To that end a
crucial component of today’s microgrid is a microgrid controller. The controller must consider forecasted
2
output of renewable distributed generation (DG) and load demand, market tariffs or forecasted electricity
and fuel prices, and the technical constraints on the interconnected electrical distribution network and
devices to provide the necessary dispatch with the microgrid. Considerable efforts have been devoted to
optimal scheduling and management of a microgrid [7]. In a past effort Oak Ridge National Laboratory
(ORNL) developed 10 microgrid operation and control use cases, which have been widely accepted by
the industry [8]. The use cases for control and operations of a microgrid are
frequency control,
voltage control (grid-connected and islanded),
grid-connected to islanding transition – intentional,
grid-connected to islanding transition – unintentional,
islanding to grid-connected transition,
energy management (grid-connected and islanding),
protection,
ancillary services (grid-connected),
black start, and
user interface and data management.
While these 10 use cases capture the key requirements of a microgrid controller, a microgrid design has
no set constraints on generation resources, demand, and network topology or system configuration. This
characteristic of a microgrid results in unique control and operational functions per microgrid and
microgrid controller, which has inherently created confusion over the microgrid control options and
functions available today. For this reason a complete list of microgrid functions supported by vendor
controllers has been developed and is presented in Sect. 2 of this report.
1.3 ADVANCED DISTRIBUTION MANAGEMENT SYSTEM
A distribution management system (DMS) is a decision support system used by distribution operators and
field operating personnel for monitoring and control of the electric distribution system in a coordinated
and efficient manner. The DMS includes a distribution supervisory control and data acquisition (SCADA)
system and various advanced applications such as an advanced metering infrastructure, an outage
management system (OMS), and a geographic information system. A typical DMS is illustrated in Fig. 1
[9].
An advanced distribution management system (ADMS) has been constructed from a DMS concept but
with additional features. The ADMS integrates energy efficiency, demand response, and distributed
resources technologies to enable grid operators to make intelligent decisions in operating the distribution
system more efficiently, reliably, and at a lower cost. This system provides electric distribution utilities
the ability to incorporate distributed energy resources, demand response, energy storage systems, and
electric vehicles, not unlike a microgrid. A microgrid is typically much smaller in size (on the megawatt
scale) as compared to a full distribution system and comprises various DGs, energy storage systems, and
responsive loads that can be operated in both a grid-connected and islanded mode. As a result many of the
ADMS/DMS vendors are attempting to expand the development of ADMS/DMS products to include
microgrid management functions. Thus, the vendor specifications on these systems were also included in
the survey.
3
SCADA = supervisory control and data acquisition
VAR = volt-ampere reactive
Fig. 1. A typical DMS.
1.4 SCOPE AND PURPOSE
At this time the absence of a recognized standard for a microgrid controller has resulted in numerous
vendor-supported microgrid controllers with various functionalities that are unique in many respects. In
most cases these controllers were developed and demonstrated for individual customers at specific
microgrid sites. As a result the current state of the microgrid controller industry has been difficult to
assess.
This report discusses the results of a recent microgrid controller survey and evaluates the survey results.
The microgrid controllers within the survey included vendor- and national-laboratory-developed
microgrid controllers. For simplification of the survey, a complete list of microgrid controller functions
was developed and delivered to survey participants. The participants then simply indicated with a “yes” or
“no” if a function was available in the vendor product (e.g., microgrid controller or DMS/ADMS). All the
survey results were collected and compiled to provide a clear indication of the state of microgrid
controllers. This information is important and valuable for identifying the necessary research in this area.
In addition, the results clearly demonstrate that DOE-funded research in microgrid controls and microgrid
controllers is unique and not competing with that of industry.
1.5 CHALLENGES
It should be noted that the survey’s objective was to identify the overall state of microgrid controllers.
However, a number of challenges had to be considered when evaluating the results.
The survey could not capture all of the unique differences of the vendor products. For example,
vendor controller communication might only be with vendor-developed assets. Any more detailed
assessment would require a much more comprehensive survey, and the information might not be
available without a nondisclosure agreement.
A full comprehensive survey of all microgrid controllers would be difficult because many vendors
consider the functionality of the microgrid controller to be business sensitive. As a means of
Advanced Metering Infrastructure (AMI)
Outage Management System (OMS)
Geographic Information System (GIS)
Advanced Applications
Data management
On-line power flow
Intelligent alarm processing
State estimation
Volt/VAR control
Switch order management
Demand Response Management
Etc.
Distribution SCADA
Real-time data acquisition
Operation alerts
Remote control
Tagging
Display real-time data
Data archiving
Etc.
Field Devices
Substation Devices
4
obtaining the survey information and protecting the confidentiality of the data, an anonymized
process was promised to remove vendor-specific details. Still, only 52 percent of the respondents
replied to the request.
Due to the inherent nature of the research involved in microgrid controllers and grid modernization,
vendors are rapidly changing the development and functionality of these controllers. Therefore,
improvements in these functions were probably already present or on the horizon.
2. MICROGRID CONTROLLER SURVEY
2.1 APPROACH
As an initial start to the survey, a complete list of functions that could be present in a microgrid was
generated for comparing the capabilities of microgrid controllers. The initial function list was constructed
based on the 10 ORNL microgrid operation and control use cases and 18 DMS functions developed by
the Institute of Electrical and Electronics Engineers (IEEE) DMS Task Force of the Smart Distribution
Working Group for the DMS-OMS State of the Industry Survey. These functions were categorized into
five groups—energy management, protection and control, resiliency, ancillary services, and data
management—as shown in Fig. 2. Each group has a particular focus or objective.
1. The functions in energy management have the primary target of supporting power balancing in
steady state.
2. The functions in protection and control support voltage and frequency control.
3. The functions in resiliency aim to increase survivability of a microgrid under disturbances or
severe weather conditions.
4. The functions in ancillary services strive to support the interaction with the local utility or
distribution system operator.
5. The functions in data management address interoperability and data management.
Each of these functions may include several subfunctions or services. Various methods or models can be
used to achieve these functions. The survey included questions on these details in an attempt to capture
the state of the art of the microgrid controllers. All the functions listed in the survey can be found in
Tables 1 through 5, and the specific definitions of these functions can be found in Appendix A.
5
DER = distributed energy resource
EV = electric vehicle
IED = intelligent electronic device
T&D = transmission and distribution
VAR = volt-ampere reactive
Fig. 2. Microgrid functions.
6
Table 1. Functions in energy management group
1 Energy
Management
1.1. Grid-Connected Energy
Balancing
Unit Commitment (UC)
(Stochastic/Robust/Deterministic?)
Economic Dispatch (ED)
(Stochastic/Robust/Deterministic?)
Optimal Power Flow (OPF)
(Stochastic/Robust/Deterministic?)
1.2. Energy Market
Participation Transactive Energy/Bidding Function
1.3. Operation Optimization
Peak Shaving/Valley Filling
Loss Minimization
Conservation Voltage Reduction
1.4. Forecast
Load Forecast
Wind Power Forecast
Photovoltaic Power Forecast
1.5. Islanding Energy
Management
UC (Stochastic/Robust/Deterministic?)
ED (Stochastic/Robust/Deterministic?)
OPF (Stochastic/Robust/Deterministic?)
Spinning Reserve/Regulation Management
1.6. Energy Storage Control
1.7. State Estimation (SE) SE for Billing
SE for Optimization and Control
1.8. Backup Plan for
Islanding Operation Contingency Analysis (Power Perspective)
1.9. Two-Way
Communication
Between Microgrid Energy Management System (EMS)
and Controllable Sources/Inverters
Between Microgrid EMS and Controllable Loads
1.10.
EV
Charging/Discharging
Management
Vehicle to Grid?
1.11. Load Balancing
1.12.
Additional Uncertainty
Management of
Renewables
1.13. Scalability Multiple Microgrids or Microgrid Network
7
Table 2. Functions in protection and control group
2 Protection and
Control
2.1. Relay Protection
Coordination
Short-Circuit Protection
Ground Protection
Fault Location, Isolation, and Service Restoration
Disturbance Logging, Time-Tagging, and Analysis
2.2. Frequency Control in
Islanding Mode
Steady-State Device Level Control (Droop/V-f/PQ
Control)
Coordinated Control of Multiple Device (Within Seconds
Level or Subseconds)
Transient Device Level Control
Frequency Smoothing
Low-Frequency Ride-Through
Emergency Load Shedding
2.3. Volt/ VAR and Reactive
Power Control
Steady-State Device Level Control (Droop/V-f/PQ
Control)
Optimal Coordinated Load Tap Changers (LTCs),
Distributed Energy Resources (DERs), and Capacitor
Banks for Voltage Profile Control (Both Grid-Connected
and Islanding State)
Cooptimization of Real and Reactive Power Considering
DER’s Real and Reactive Power Capability
Management of Voltage Fluctuations Due to Intermittent
DERs
Low-Voltage Ride-Through
2.4. Grid-Connected to
Islanding Transition
Intentional Islanding Transition
Unintentional Islanding Transition
2.5. Islanding to Grid-
Connected Transition
Black Start
Synchronization
Table 3. Functions in resiliency group
3 Resiliency
3.1. Severe Weather Forecast Storm/Hurricane/Extreme Temperature?
3.2.
Uninterrupted Power
Supply (UPS) Function for
Critical Load (Intelligent
Load Shedding)
3.3.
Coordinate Distributed
Energy Resources with
Microgrid Reconfiguration
3.4. Backup Plan Backup Resilient Islanding Operation Plan for Certain
Outage Period (Energy)
8
Table 4. Functions in ancillary services group
4 Ancillary
Services
4.1. Day-Ahead Demand
Response Price-Driven Day-Ahead Demand Response
4.2. Real-Time Demand
Response Price-Driven Real-Time Demand Response
4.3. Utility Event Response Active Power/Reserve?
4.4.
Transmission and
Distribution Congestion
Management (Network
Restoration, Dynamic Line
Rating)
4.5. Regulation Service Frequency
4.6. Spinning Reserve Support
4.7. Phase Balancing
4.8. Provision of Requested
Supports
VAR Support
Watt Support
Power-Factor Support
Black-Start Capacity
Table 5. Functions in data management group
5 Data
Management
5.1.
Intelligent Electronic Device
(IED) Functions Based on
International Standards for
Interoperability
IEC 61850 or else
5.2.
Database Server Design for
Interoperable IED Data
Gathering
5.3. User Authentication
5.4. Event Logging
5.5. Security Issue Reporting
5.6. Alarms
5.7. Field Sensors &
Measurements Infrastructure
All of these functions were inserted into a Microsoft Excel form and sent to participants. The participant
list consists of active members of the IEEE P2030.7 Distribution Resources Integration Working
Group/Microgrid Controllers Task Force. The task force members primarily consist of microgrid
controller or ADMS/DMS vendors and consultants actively involved in microgrid controller research and
development (R&D). The survey did not include utility operators or representatives of colleges or
universities. The survey participants are listed in Table 6.
9
Table 6. Survey participants
Company Name Company Name Company Name
ABB ETAP Power Analytics
Advanced Control Systems General Electric Schneider
Alstom Grid Green Energy Corp Siemens
Blue Pillar Intelligent Power & Energy
Research Corporation Spirae
Eaton
Lawrence Berkeley National
Laboratory (Distributed Energy
Resources Customer Adoption
Model)
Sustainable Power Systems
Encorp Opus One Solutions Toshiba
Enphase Energy
Oak Ridge National Laboratory
(Complete System-Level
Efficient and Interoperable
Solution for Microgrid Integrated
Controls)
Viridity Energy
As a means of increasing the number of respondents and avoiding burdening participants with too many
questions and significant work, participants were asked to put “Y” or “N” to indicate whether each
specific function was included in a listed product. The names of the known vendor products were
specified, but the vendors were allowed to add columns for other products and provide further
specifications on the responses. A sample screenshot from the survey is shown in Fig. 3.
10
Fig. 3. Sample screenshot from survey.
The main objective of this survey was to evaluate the overall status of the microgrid controller as a guide
for R&D in this area. Therefore, after feedback was received, the names of the vendors and products were
removed to provide anonymity to all participants.
2.2 SURVEY RESULTS
The survey was first distributed in November 2014. Because the number of members of IEEE P 2030.7
had grown, the survey was redistributed in March 2015. The latest feedback was collected in June 2015.
The survey Excel form was emailed to all 21 organizations and vendors listed in Table 6. Currently, 11 of
these organizations have participated in the survey. The original survey results from these 11 vendors
were anonymized and compiled into a single table for easy comparison. The results are shown in
Appendices B through F.
According to the survey results, the functions that have been included in most of the microgrid controllers
include
economic dispatch for grid-connected and islanded modes (9),
peaking shaving (10),
11
loss minimization (8),
reserve management (9),
two-way communication (8),
emergency load shedding (10),
islanding (9),
resynchronization (8),
uninterruptible power supply (UPS) function for critical load (9), and
provision of requested support (9).
Generally, as basic functions of a microgrid controller, islanding and resynchronization functions are
included within most vendor microgrid controller products. These two basic functions are highly
interwoven with other functions and have also been developed in commercial products. For example,
emergency load shedding is an easy way to quickly regain the balance between load and generation
during islanding transition. Economic dispatch and reserve management are necessary functions for
operating efficiently and reliably off-grid. Peak shaving, loss minimization, and UPS functions for critical
load use the flexibility of local resources and support the end-use customers in grid-connected mode. All
of these functions rely on an efficient two-way communication system.
Functions that have not been included in most of the microgrid controllers include
conservation voltage reduction (3),
state estimation (5),
contingency analysis (6),
electrical vehicle management (4),
transient device level control (4),
low-frequency ride-through (3),
low-voltage ride-through (3),
severe weather forecast (3), and
transmission and distribution congestion management (3).
Only a small number of vendors have considered these functions in their products. These functions are
more advanced and require complicated control and optimization algorithms. In addition, the realization
of the basic functions (islanding and resynchronization) does not rely on these advanced functions.
The survey results would suggest that many of the microgrid controllers are similar and that all of the
functions have been derived. While vendors have laid claims to supporting these functions, a true
comparison of the ability of a microgrid controller to perform these actions can only be demonstrated at
real microgrids or microgrid testbeds [10], which is beyond the scope of this report.
ORNL has been actively developing an open-source microgrid controller to demonstrate the microgrid
functions and provide a base case for comparison with other microgrid controllers. This microgrid
controller, the Complete System-Level Efficient and Interoperable Solution for Microgrid Integrated
Controls (CSEISMIC), currently consists of an energy management system (EMS) and a SCADA system.
This architecture was developed in 2015 and allowed comparison to vendor microgrid controllers.
Although inheriting some functions and terminologies from SCADA and EMS, CSEISMIC has
significant differences from commercial microgrid controllers due to special characteristics and operation
strategies.
The CSEISMIC SCADA not only communicates with individual devices and collects data (like EMS
or DMS) but also has real-time control functions such as voltage and frequency regulation in islanded
12
mode, low-voltage/-frequency ride-through, energy storage management as well as DER, and demand
response coordination [11].
The CSEISMIC EMS performs 5 min. look-ahead optimal power flow, which optimizes P and Q
simultaneously, whereas most of commercial products optimize P and Q separately [12]. The
CSEISMIC approach is especially important in a microgrid because the resources in a microgrid are
limited, and a lot of them are resources of both real and reactive power.
The CSEISMIC EMS uses state-of-the-art optimization algorithms to take uncertainties of renewable
sources and loads into account [13]. Proper management of these algorithms that takes into accounts
their correlations and demand response will contribute a major value stream to microgrid controllers
and encourage the deployment of microgrid technology.
The CSEISMIC microgrid controller uses a three-phase unbalanced system model for control and
optimization of microgrids, while most commercial microgrid controllers use a single-line balanced
model. The three-phase unbalanced system model has introduced more interesting characteristics and
challenges [14, 15].
The current architecture of CSEISMIC is rapidly being replaced with a new one that supports distributed
communications and controls. Unlike traditional bidirectional communication between devices in which
one device issues a query and a secondary device responds, the new architecture is built on the Data
Distribution Service (DDS), which is a publish/subscribe protocol that enables multiple devices to write
and read from the same topic. This subscription-based architecture reduces communication bandwidth
requirements and simplifies the addition of devices to the overall microgrid topology. Furthermore, the
auto-discovery feature provided by DDS eliminates the need to establish connections to predetermined
devices, thereby effectively adapting to the field implementation of the microgrid without requiring time-
consuming edits to the code base, device whitelists, or configuration files.
On another note, the current development stages of the ORNL microgrid controller are focusing on more
distributed control architecture. A service-oriented architecture for microgrid control and operation is
currently under development to allow plug-and-play solutions. Advanced optimization techniques will be
developed to encompass larger systems and utilize emerging technologies such as the internet of things,
machine learning, real-time hardware in the loop, etc. The next version of CSEISMIC will create an open
microgrid reference platform to accelerate research in control, optimization, standards development, and
cyber-physical security.
CONCLUSION
This report discussed the results of a recent microgrid controller survey and evaluated the survey results.
First, a complete list of functions that could be present in a microgrid was generated for comparing the
capabilities of microgrid controllers. A survey form in Microsoft Excel was sent to vendors and national
laboratories with microgrid controller products. All feedback was aggregated and analyzed in this report.
The results showed the current status of microgrid controllers in the market. The R&D needs in this area
have been discussed based on the results. In addition, this work clearly demonstrated that CSEISMIC and
DOE–funded research in microgrid controllers is significantly different from that related to commercial
microgrid controllers. Thus, DOE–funded microgrid controller research is unique and not competing with
that of industry.
13
REFERENCES
1. Office of Electricity Delivery and Energy Reliability Smart Grid R&D Program, DOE Microgrid
Workshop Report (US Department of Energy, August 2011). Available online at
http://energy.gov/sites/prod/files/Microgrid%20Workshop%20Report%20August%202011.pdf
2. A. G. Madureira and J. A. Pecas Lopes, "Coordinated voltage support in distribution networks with
distributed generation and microgrids," IET Renew. Power Gen. 3, no. 4 (Dec. 2009):439–454.
3. S. Beer, T. Gomez, D. Dallinger, I. Momber, C. Marnay, M. Stadler, and J. Lai, "An economic
analysis of used electric vehicle batteries integrated into commercial building microgrids," IEEE
Trans. Smart Grid, 3, no. 1 (Mar. 2012): 517–525.
4. A. G. Tsikalakis and N. D. Hatziargyriou, "Centralized control for optimizing microgrids operation,"
IEEE Trans. Energy Convers. 23, no. 1 (Mar. 2008): 241–248.
5. C. Marnay, "Microgrids and Heterogeneous Security, Quality, Reliability and Availability," in Proc.
Power Convers. Conf. (2007): 629–634.
6. M. Agrawal and A. Mittal, “Micro grid technological activities across the globe: A review,” Int. J.
Res. Rev. Appl. Sci. 7, no. 2 (May 2011): 147–152.
7. W. Gu, Z. Wu, R. Bo, W. Liu, G. Zhou, W. Chen, and A. Wu, "Modeling, planning and optimal
energy management of combined cooling, heating and power microgrid: A review," Int. J. Electr.
Power Energy Syst. 54 (Jan. 2014): 26–37.
8. Y. Xu, G. Liu, and J. Reilly, ORNL microgrid use cases, July 2014. Available online at
http://smartgrid.epri.com/Repository/Repository.aspx
9. EPRI Report, Integrating Smart Distributed Energy Resources with Distribution Management
Systems, September 2012.
10. B. Xiao, K. Prabakar, M. Starke, G. Liu, K. Dowling, B. Ollis, P. Irminger, Y. Xu, and
A. Dimitrovski, "Development of Hardware-in-the-loop Microgrid Testbed," in Proceedings of IEEE
Energy Conversion Congress and Exposition (ECCE 2015) Montreal, Canada, Sept. 20–24, 2015.
11. Y. Xu, H. Li, and L. M. Tolbert, "Inverter-based microgrid control and stable islanding transition,"
Energy Conversion Congress and Exposition (ECCE), 2012 IEEE (Raleigh, NC, 2012): 2374–2380.
12. G. Liu, M. Starke, X. Zhang, and K. Tomsovic, “A MILP-Based Distribution Optimal Power Flow
Model for Microgrid Operation,” in Proceedings of the 2016 IEEE PES General Meeting (Boston,
MA, July 17–21, 2016).
13. G. Liu, Y. Xu, and K. Tomsovic, "Bidding Strategy for Microgrid in Day-ahead Market based on
Hybrid Stochastic/Robust Optimization," IEEE Transactions on Smart Grid, 7, No. 1 (Jan. 2016):
227–237.
14. G. Liu, O. Ceylan, Y. Xu, and K. Tomsovic "Optimal Voltage Regulation for Unbalanced
Distribution Networks Considering Distributed Energy," in Proceedings of the 2015 IEEE PES
General Meeting (Denver, CO, Jul. 26–30, 2015).
14
15. G. Liu, O. Ceylan, M. Starke, and K. Tomsovic, "Advanced Energy Storage Management in
Distribution Network," in Proceedings of the 49th Hawaii International Conference on System
Sciences (HICSS-49) (Kauai, HI, Jan. 5–8, 2016).
A-1
APPENDIX A. MICROGRID FUNCTION DEFINITIONS
Microgrid Function Description
Grid-connected Energy
Balancing
This is a group of functions including unit commitment, economic dispatch, and optimal
power flow
Unit Commitment Schedule the start-up and shunt-down sequence of generators
Stochastic/Robust/Dete
rministic
The optimization model considers stochastic optimization, robust optimization or
deterministic optimization.
Optimal Power Flow Determines the real and reactive power output for interconnected generators within the
system.
Transactive Energy Microgrid controller is able to bid into the energy market or transact with another entity.
Loss Minimization Minimizes the power loss within the distribution network.
Conservation Voltage
Reduction
Reduces the voltage to the lower half of allowed voltage range to decrease the load
consumption
Reserves Quantifies the amount of needed spinning reserve and regulation capacity and dispatches
the generators or responsive loads when islanded accordingly
Energy Storage Control Controlling and optimizing the charging and discharging of energy storage systems.
State Estimation Estimates the condition of system and validates with redundant measurements
Backup Plan for
Islanding Operation
Preparation of islanding operation and ensuring that enough power capacity is available.
Contingency Analysis
(Power Perspective):
Performing the system failure analysis for n-1 or n-2 failures
Load Balancing Balancing the load between different feeders
Uncertainty
Management of
Renewables
Any special program for handling the uncertainty of renewables and load.
Scalability Application for multiple microgrids and different sizes of microgrids
Coordinated Control of
Multiple Device
Real power coordination of devices for voltage regulation
Optimal Co-ordinated
LTCs, DERs, and
Capacitor Banks for
Voltage Profile Control
(Both Grid-connected
and Islanding State)
Coordination of controllable devices in distribution network, such as LTCs, DERs and
capacitor banks
Coordinate DERs with
Microgrid
Reconfiguration
Restoration considering DERs.
Backup Resilient
Islanding Operation
Plan for Certain
Outage Period
(Energy):
Preparation of islanding operation, have enough energy for critical loads surviving for
certain time period.
B-1
APPENDIX B. MICROGRID FUNCTIONS COMPARISON ENERGY MANAGEMENT
Company Name ORNL A B C D E F G H I J
Microgrid Controller or ADMS A.1 A.2 B.1 C.1 C.2 C.3 D.1 E.1 F.1 F.2 G.1 G.2 H.1 H.2 H.3 I.1 I.2 J.1
MGF Subfunctions
Grid-connected Energy Balancing
Unit Commitment Y1 Y3 Y1 Y Y Y Y Y1 Y
Economic Dispatch Y1 Y3 Y1 Y Y Y Y1 Y
Optimal Power Flow Y1 Y Y4 Y5 Y Y Y
Energy Market Transactive Energy Y Y Y Y Y6
Operation Optimization
Peak Shaving Y Y Y Y7 Y Y Y Y Y8 Y Y Y
Loss Minimization Y Y Y Y9 Y Y Y Y Y
CVR
Y Y10 Y
Forecast
Load Forecast Y Y Y11 Y Y Y Y Y Y
Wind Power Forecast
Y12 Y Y
PV Power Forecast Y Y12 Y Y Y Y Y Y
Islanding Energy Management
Unit Commitment Y1 Y Y13 Y1 Y Y Y Y Y1 Y
Economic Dispatch Y1 Y Y13 Y1 Y Y1 Y14 Y Y Y1 Y1 Y
Optimal Power Flow Y1 Y2 Y Y15 Y Y Y
Reserves Y Y Y16 Y Y Y Y Y Y Y Y
1 Deterministic. 2Basic. 3Using heuristic rules for microgrid controllers; and DRMS for DMS 4Using DRMS for DMS 5Robust 6Manual 7As distributed control system function for microgrid controllers; and through automated
capacitor and regulator control to reduce peak demand as DMS function 8peak shaving only
9Voltage and Var Optimization or Feeder Reconfiguration DMS applications 11Using DMS load profiles where the forecast is provided by an external system 12 DMS function using generation profiles with the forecast provided by an external
system 13 heuristic rule for microgrid controllers 14partial, deterministic 15 Robust, back upstream 16
distributed control system microgrid controllers function
B-2
Company Name ORNL A B C D E F G H I J
Microgrid Controller or ADMS A.1 A.2 B.1 C.1 C.2 C.3 D.1 E.1 F.1 F.2 G.1 G.2 H.1 H.2 H.3 I.1 I.2 J.1
MGF Subfunctions
ES Control Y Y Y16 Y Y Y17 Y5 Y Y Y Y17 Y Y
State Estimation (SE)
Billing Y Y
Optimization/Control Y Y Y18 Y Y19 Y Y
Backup Plan for Islanding Operation
Contingency Analysis Y Y20 Y Y Y Y
Two-way Communication
EMS/Sources Y Y Y Y21 Y Y Y Y Y Y Y Y Y Y
EMS/ Loads Y Y Y Y21 Y Y Y22 Y Y Y Y22 Y22 Y
Electric Vehicle Vehicle to Grid (V2G)
Y23 Y Y Y
Load Balancing Y Y Y Y24 Y Y Y Y Y Y Y Y Y Y
Uncertainty Management Renewables Y Y Y25 Y Y26 Y Y
Scalability Multiple Microgrids or Microgrid Network
Y Y Y Y Y Y27 Y28 Y Y27 Y27
17 limited capabilities 18 DMS function using Load Allocation or State Estimator 19 converging with SCADA and AMI data 20 as a DMS function 21 Modbus RTU for microgrid controllers 22 depends upon load controller
23 Using DRMS but no support for V2G 24 microgrid controller function 25 Using forecast profiles and power flow modeling of DER in DMS 26 online connection impact assessments 27 to some extent 28 substation, feeder, community, customer, or sub-customer microgrids
C-1
APPENDIX C. MICROGRID FUNCTIONS PROTECTION AND CONTROL
Company Name ORNL A B C D E F G H I J
Microgrid Controller or ADMS A.1 A.2 B.1 C.1 C.2 C.3 D.1 E.1 F.1 F.2 G.1 G.2 H.1 H.2 H.3 I.1 I.2 J.1
MGF Subfunctions
Relay Protection
Coordination
Short-Circuit Protection
Y Y Y Y1 Y Y Y Y
Ground Protection Y Y1 Y Y Y Y
Fault Location, Isolation & Service Restoration (FLISR)
Y Y Y2 Y
Y Y Y
Disturbance Logging, Time-Tagging and
Analysis Y Y Y3 Y Y Y Y Y Y
Frequency Control in Islanding
Mode
Steady state Device Level Control
(Droop/V-f/PQ control)
Y Y Y Y4 Y Y Y5 Y Y6 Y
Coordinated Control of Multiple Device
(Within Seconds level or Subseconds)
Y Y
Y7 Y Y Y Y Y Y Y Y Y
Transient Device Level Control
Y Y Y7 Y
Frequency Smoothing Y4 Y Y8 Y9 Y Y Y8 Y
Low Frequency Ride-Through (LFRT)
Y Y Y10
Emergency Load shedding
Y Y Y Y11 Y Y Y Y Y Y Y Y Y
1 using manual short-circuit analysis in DMS
2 as a DMS function
3 Logging and time-tagging all power signals from all devices in microgrid control system;
Using SCADA historian logging of SCADA monitored events in DMS 4 microgrid controller function
5 with power conversion system, PCS
6 MGMS supports it, but doesn't control itself
7 through microgrid controller distributed system architecture
8 as a Load Shedding function
9 load shedding and DER dispatch
10 with PCS
11 using feeder overload shedding function of microgrid control system; and SCADA load
shedding application for DMS
C-2
Company Name ORNL A B C D E F G H I J
Microgrid Controller or ADMS A.1 A.2 B.1 C.1 C.2 C.3 D.1 E.1 F.1 F.2 G.1 G.2 H.1 H.2 H.3 I.1 I.2 J.1
MGF Subfunctions
Volt/Var Control
Steady state Device Level Control
(Droop/V-f/PQ control)
Y Y18 Y Y4 Y Y Y Y Y Y
Optimal Co-ordinated LTCs, DERs, and
Capacitor Banks for Voltage Profile
Control(Both Grid-connected and Islanding State)
Y Y Y12 Y Y Y Y
Co-optimization of Real and Reactive Power Considering
DRE’s Real and Reactive Power
Capability
Y Y Y12 Y Y Y Y Y
Management of Voltage Fluctuations due to Intermittent
DERs
Y Y Y13 Y14 Y Y
Low Voltage Ride-Through (LVRT)
Y Y10 Y
Grid-connected to
Islanding Transition
Intentional Islanding Transition
Y Y Y15 Y Y Y Y10 Y Y Y Y Y
Unintentional islanding transition
Y Y Y15 Y Y17 Y10 Y Y Y17 Y
Islanding to Grid-
connected Transition
Black Start Y Y Y4 Y Y Y10 Y Y Y Y Y
Synchronization Y Y Y16 Y Y Y10 Y Y Y Y Y
12 Using VVO application in DMS, DER is modeled with capacitor and regulator controls
13 Using VVO voltage violation enforcement
14 using ESS
15 microgrid controllers function; and using temporary source energization in DMS
16 microgrid controllers via f/V setpoints, and via protection relay with sync check
17 through fast load shed
18 Basic
D-1
APPENDIX D. MICROGRID FUNCTIONS RESILENCY
Company Name ORNL A B C D E F G H I J
Microgrid Controller or ADMS A.1 A.2 B.1 C.1 C.2 C.3 D.1 E.1 F.1 F.2 G.1 G.2 H.1 H.2 H.3 I.1 I.2 J.1
MGF Subfunctions
Severe Weather Forecast
Storm/Hurricane/Extreme Temperature?
Y Y Y Y N
UPS Function for Critical Load (Intelligent Load Shedding)
Y Y Y Y1 Y Y Y Y Y Y Y Y
Coordinate DERs with Microgrid Reconfiguration
Y Y Y2 Y Y Y3 Y3 Y Y Y Y3 Y
Backup Plan
Backup Resilient Islanding Operation Plan for Certain Outage Period(Energy)
Y Y Y Y Y Y Y
1Using DMS SCADA Load Shedding application 2Using power flow analysis and temporary source energization in DMS 3limited
E-1
APPENDIX E. MICROGRID FUNCTIONS ANCILLARY SERVICES
Company Name ORNL A B C D E F G H I J
Microgrid Controller or ADMS A.1 A.2 B.1 C.1 C.2 C.3 D.1 E.1 F.1 F.2 G.1 G.2 H.1 H.2 H.3 I.1 I.2 J.1
MGF Subfunctions
Day-ahead Demand Response
Price Driven Day-ahead Demand Response
Y Y1 Y Y Y Y Y N
Real-Time Demand Response
Price Driven Real-Time Demand Response
N Y2 Y Y Y Y Y Y
Utility Event Response
Active power/reserve?
Y Y Y3 Y Y Y Y Y Y Y Y
T&D Congestion Management (Network restoration, dynamic line rating)
N Y4 Y
5 Y
Regulation Service
(Frequency) N Y6 Y Y Y Y Y Y Y
Spinning Reserve Support Y Y7 Y Y Y Y
Phase Balancing N Y8 Y
9 Y
Provide Requested Supports
Var Support Y Y Y10
Y Y Y Y Y Y Y Y Y Y
Watt Support Y Y Y11
Y Y Y Y Y Y Y Y Y Y
Power Factor Support Y Y Y12
Y Y Y Y Y Y Y Y Y Y
Black-Start Capacity Y Y Y Y Y Y13
Y Y Y Y Y
1 Using DMS in conjunction with DRMS
2 AMI integration in DMS and demand response, with DRMS 3 P/Q lopping in grid-connected mode, f/V support for utility fluctuations for microgrid
controllers; and using VVO Demand Reduction or Load Transfer application in DMS 4 Using capability in Restoration Switching Analysis, Line Unloading , and dynamic
transformer ratings functions of DMS 5 alternate transfer capacity 6 microgrid controller function 7 distributed control system microgrid controllers function
8 Using phase balancing capability in Feeder Reconfiguration application in DMS 9 if single-phase resources available 10 by microgrid controllers via Q setpoints, and using VVO voltage and capacitor
setpoints in DMS 11 by microgrid controllers via P setpoints 12 by microgrid controller p.f. correction 13 with PCS
F-1
APPENDIX F. MICROGRID FUNCTIONS GRAPHICAL USER INTERFACE AND DATA
MANAGEMENT
Company Name ORNL A B C D E F G H I J
Microgrid Controller or ADMS A.1 A.2 B.1 C.1 C.2 C.3 D.1 E.1 F.1 F.2 G.1 G.2 H.1 H.2 H.3 I.1 I.2 J.1
MGF Subfunctions
IED Functions Based on International Standards for Interoperability
IEC 61850 or else Y1 Y Y Y2 Y Y3 Y3 Y Y Y3 Y5 Y
Database Server Design for Interoperable IED Data Gathering
N Y Y Y4 Y Y Y Y Y Y Y6
User Authentication Y Y Y Y7 Y Y Y Y Y Y Y Y Y Y Y Y Y
Event Logging Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y
Security Issue Reporting Y Y Y Y Y Y Y Y Y Y Y Y Y
Alarms Y Y Y Y8 Y Y Y Y X Y Y Y Y Y Y Y Y
Field Sensors & Measurements Infrastructure
Y Y Y Y9 Y Y Y Y Y Y Y Y
1Modbus 2Modbus for microgrid controllers; DNP3, IEC 60870-5-104, CIM for DMS 3 68150 and DNP 4 trending/historian data storage for microgrid controllers, using SCADA DNP 3.0 for
DMS 5 DNP
6 PI interface 7 VPN/SSH/Password HMI 8 SCADA/HMI 9 meter/analog inputs for microgrid controller; DNP3 field sensors for DMS
